At DataGrail, we believe privacy is a human right. We believe every individual should have control over their identity and personal data. This is one of today’s most important challenges.The world’s best brands understand this–they’re built on trust. We help the most trusted brands like Databricks, HashiCorp, and other known and admired organizations. We’re looking for a Machine Learning Engineer to help us continue to deliver products that solve our customers’ most important privacy challenges.

In this role, you’ll help us transform the privacy space from a world of compliance to one that is proactive about managing privacy risk and giving users more control over their data.

This is a great opportunity to solve these challenges at scale in a small, agile, and growing company with impressive growth rates and trajectory working closely with our Co-founder and a team of cross-functional individuals that are passionate about building the most trusted privacy platform.


Our mission is to give our customers back control over their data, so they can continue to focus on growing their brands and the relationships with their customers who, more than ever, demand more transparency and control. That starts with knowing where the data is and what it is. Humans can’t do this accurately at scale when they have hundreds of systems, thousands of tables/datasets, and potentially millions of columns or data elements. You’ll help us build and productize state-of-the-art machine learning models that classify personal data across internal and third-party data sources and rethink ways to minimize its inherent risk with privacy by design principles.

The Skill Set:

  • Consider yourself and expert in machine learning, deep learning, and statistical modeling techniques
  • Creative problem solver who values analyzing and tackling complex dataset
  • Proficient with programming languages like Python or similar
  • Use machine learning frameworks and libraries including TensorFlow, PyTorch, and/or scikit-learn
  • Pragmatic about the latest developments with foundation models like LLMs and their applications
  • Collaborate with cross-functional teams to build great products that drive value for our customers, not just impressive technical solutions
  • Bias for action and tight feedback loops with measurable business impact
  • Sound understanding of data processing and storage technologies, including SQL and NoSQL databases

Within 90 Days You’ll:

  • Familiarize yourself with DataGrail’s privacy management platform and its core functionalities 
  • Gain an understanding of DataGrail’s existing machine learning infrastructure, models, and algorithms
  • Collaborate with the team and identify areas of improvement and optimization in the machine learning pipeline
  • Take ownership of  assigned machine learning projects and drive them from ideation to implementation
  • Improve the performance and accuracy of machine learning models by incorporating feedback and iterating on existing models

Within 180 Days You’ll:

  • Collaborate with the data engineering team to optimize data pipelines and ensure the availability of high-quality data for training and evaluation
  • Contribute to the development and maintenance of machine learning infrastructure and tools
  • Actively participate in team discussions and knowledge sharing session to foster a culture of learning and growth
  • Develop a strong understanding of data privacy regulations and their impact on businesses

Within 365 Days You’ll:

  • Drive research and development efforts to explore new machine learning techniques and algorithms applicable to data privacy compliance
  • Identify opportunities to leverage machine learning to enhance the overall functionality and capabilities of the DataGrail platform
  • Collaborate with the product management team to translate customer requirements into machine learning solutions
  • Contribute to the thought leadership within the industry by publishing research papers, presenting at conferences, or participating in relevant community events


Please note that the compensation range below is a guideline and final compensation will be based on factors such as qualifications, skill level, and competencies.

Compensation Range
$180,000$200,000 USD
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